Delivering Machine Learning Foundations I and II to groups of 20-80 Amii clients on a monthly basis.
Teaching 2-3 students weekly about concepts to from Foundations of Computation, Formal Systems and Logic, and Algorithms I.
Planning, developing, recording, and delivering lecture and workshop content for the AIMSS Artificial Intelligence in Medicine course.
Teaching 2-3 students weekly about concepts to from Foundations of Computation, Formal Systems and Logic, and Algorithms I.
I was invited to participate in a fireside conversation (broadcast over 150 young women and non-binary people) to kick off the 2022 Amii Kickstart program. Kickstart, (previously AlbertaWomen.AI when I participated back in 2019/20), is an effort to bring together academic and early-career gender minorities with an interest in AI to foster a sense of connectedness and community. More can be read about my experience with Kickstart here, here, and here.
Presenting an hour-long session to 23 PPPH employees about how Large Language Models work, the recent LLM-driven AI-race, and best practices for LLM use in work and personal life
Contributing my thoughts and experiences about the unique overlap between rapidly developing AI systems and gender equality, hiring practices, and identity
Guiding a conversation between representatives from CPSA, CRNA, and OIPC about the present context of Health AI regulation at the 2024 Upper Bound Conference
Introducing 25 PPPH employees to the syntax and structure of Python, explaining how to set up one's Python work environment, and performing a live demonstration of basic coding and data structure principles
Providing intuition, reviewing common definitions, and discussing examples about machine learning (in the context of public health and beyond) during an AHS Lunch & Learn session attended by 25 PPPH team members
Conducting a panel about tips, tricks, and current hiring practices in the AI world for young women and gender minorities entering the job market
Discussing the barriers towards practical health AI adoption and how Individual Survival Distributions are a step in the right direction
Presenting how survival algorithms can improve hospital readmission prediction at the 2023 Upper Bound conference
Discussing the barriers towards practical health AI adoption and how Individual Survival Distributions are a step in the right direction
Presenting the work foundational to my thesis project in hospital readmission prediction at the 2023 University of Alberta Reverse Expo, winning second prize for best poster
Sharing the insights, challenges, and triumphs surrounding the 150-person Managing AI Risk project undertaken by the Vector Institute
Describing some of the unique challenges associated with using Plantae STARR-sequencing data for machine learning tasks, communicating my past and future research directions in this area
Facilitating an informative conversation with academic and early-career female role models meant to benefit high-school-aged WISEST Summer Research Program Participants
Answering questions from over 20 young scientists participating in the High School Internship and the WISEST Summer Research programs, sharing my perspectives on making the most of a science undergraduate degree
Carefully evaluating (and asking questions about) interdisciplinary talks and posters during the second annual Eureka Undergraduate Research Symposium
Helping high-school-aged Summer Career Camp participants develop their informational interview skills by participating in mock interviews and providing constructive feedback
Explaining and compiling many uses and application of survival analysis and prediction algorithms in the healthcare system
Facilitating morning and afternoon panels as part of the 2021 Science, Engineering, and Technology Conference, an event attended by young women and non-binary individuals interested in STEM fields
Speaking to a small group of AI4Good Alumni about my journey into and through graduate school, sharing advice from my experiences with the goal of encouraging gender minorities to enroll in technical graduate programs
Delivering a condensed 1.5-hour version of Machine Learning Foundations I and II to 50 students and researchers at the Canadian Symposium for Computational Neuroscience
Participating in a fireside chat to discuss my experiences as an Amii apprentice and answer questions from ~20 curious CMPUT 466/566 students
Showcasing deep-transfer-learning convolutional models for Canola gene expression prediction and appropriate baselines to use for chromosomal and organellar genomes
Carefully evaluating (and asking questions about) interdisciplinary talks and posters during the inaugural Eureka Undergraduate Research Symposium
Sharing the four main ways AIMSS contributes value to our community by creating common ground between computing science, medicine, and many other fields
Delivering a short presentation showcasing the work done by the five-person group "Angry Nerds" near the end of Introduction to Machine Learning (CMPUT 566).
Covering topics such as EMRs, imaging, video, genetics/omics, EEG, drug discovery, and protein folding through the lens of artificial intelligence applications
Delivering slides and a workshop relating to the process of data loading, exploration, visualization, and transformation
Delivering slides and a workshop relating to the use of Google Colab and Google Drive for learning and prototyping ML models
Appearing on a rotating panel as part of the 2020 Science, Engineering, and Technology Conference, giving advice to over 50 young women and non-binary individuals interested in technical fields
Illustrating how pre-trained word embeddings used to represent sentences can beat sophisticated architectures in textual similarity tasks
Speaking about how spatial variation in search engine queries or Twitter posts can help us model the spread of COVID-19
Delivering a presentation about the intersection of machine learning, medicine, and business to 30 upper-level undergraduate business students
Presenting how interprerable patterns may be extracted from multi-cancer transcriptome datasets at the 2020 Calgary Women in Data Science (WiDS) Conference
Exploring how the fields of explainability and interpretability within machine learning relate to the domain of medical artificial intelligence applications
Providing a quick first glimpse into the world of machine learning and data mining to high-school-aged young women interested in research
Delivering a presentation about the significance, mechanisms, and future of research and applications involving the CRISPR-Cas9 gene-editing procedure
Appearing on an hour-long three-person panel to share, with approximately 20 attendees, my experience in a technical field as a queer, femme-presenting individual
Surveying how Latent Dirichlet Allocation can be used for exploring biopsy membership to different gene expression "topics"